Data Engineer I

19 hours ago

Greater Bengaluru Area, India Licious Full time

SDE 1 – Data Platform Engineer Overview We are looking for a passionate and motivated Software Development Engineer (SDE 1) – Data Platform to join our growing Data Platform Engineering team at Licious. In this role, you’ll design, build, and optimize data systems and pipelines that fuel analytics, reporting, and data-driven decision-making across the organization. You’ll work on modern data platforms, collaborate with experienced engineers, and gain hands-on exposure to cutting-edge data and cloud technologies. This opportunity is ideal for someone who enjoys solving complex data problems, working with large-scale systems, and continuously learning in a fast-paced, high-impact environment. What You’ll Do Data Pipelines & Infrastructure - Design and develop scalable ETL/ELT pipelines and workflows using orchestration tools such as Airflow, Azkaban, or Luigi. - Build batch and real-time data processing systems using technologies like Apache Spark, Flink, Kafka, and Debezium. - Implement data quality, observability, and lineage frameworks to ensure reliable, accurate, and trusted data delivery. Data Management & Optimization - Develop and maintain data ingestion, transformation, and storage layers using modern data lake and warehouse platforms (AWS S3, Redshift, Snowflake, Databricks). - Write and optimize SQL queries and data models to support analytical and reporting workloads. - Collaborate with senior engineers to enhance system performance, scalability, and cost efficiency. Collaboration & Delivery - Partner with data analysts, ML engineers, and product teams to translate business needs into scalable data solutions. - Work closely with platform and DevOps teams to ensure secure, efficient, and automated data operations. - Participate in code reviews, maintain high-quality documentation, and follow software engineering best practices. Continuous Learning - Stay updated with emerging data technologies, frameworks, and cloud solutions. - Contribute to initiatives in data standardization, governance, and automation to strengthen the organization’s data foundation. What You’ll Bring Technical Skills : - Strong understanding of data engineering fundamentals — ETL/ELT design, data modeling, warehousing, and lake architectures. - Hands-on experience with one or more data technologies such as Spark, Kafka, or Airflow. - Proficiency in Python, Java, or Scala for data engineering and automation tasks. - Strong SQL skills and familiarity with relational databases (e.g., MySQL, PostgreSQL). - Exposure to cloud environments, preferably AWS, including services like S3, Glue, Redshift, EMR. Foundational Knowledge : - Understanding of software engineering practices — version control (Git), testing, CI/CD, and documentation. - Basic awareness of data governance, observability, and quality monitoring concepts. Soft Skills : - Strong analytical thinking and problem-solving mindset. - Collaborative and eager to learn from experienced mentors. - Detail-oriented, reliable, and driven to build scalable, high-performance systems. Preferred Qualifications : - Experience or exposure to data lakehouse architectures. - Familiarity with containerization (Docker) and orchestration (Kubernetes). - Understanding of MLOps, data observability, or data catalog frameworks. - Prior experience in high-growth, consumer-tech, or digital-first environments.

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